On Feb 5, 2012, at 9:54 AM, jim holtman wrote:
Is this what you are after:
x <- c(1327211358, 1327221999, 1327527296, 1327555433, 1327701042,
+ 1327761389, 1327780993, 1327815670, 1327822964, 1327897497,
1327897527,
+ 1327937072, 1327938300, 1327957589, 1328044466, 1328127921,
1328157588,
+ 1328213951, 1328236836, 1328300276, 1328335936, 1328429102)
x <- as.POSIXct(x, origin = '1970-1-1')
x
[1] "2012-01-22 05:49:18 EST" "2012-01-22 08:46:39 EST" "2012-01-25
21:34:56 EST"
[4] "2012-01-26 05:23:53 EST" "2012-01-27 21:50:42 EST" "2012-01-28
14:36:29 EST"
[7] "2012-01-28 20:03:13 EST" "2012-01-29 05:41:10 EST" "2012-01-29
07:42:44 EST"
[10] "2012-01-30 04:24:57 EST" "2012-01-30 04:25:27 EST" "2012-01-30
15:24:32 EST"
[13] "2012-01-30 15:45:00 EST" "2012-01-30 21:06:29 EST" "2012-01-31
21:14:26 EST"
[16] "2012-02-01 20:25:21 EST" "2012-02-02 04:39:48 EST" "2012-02-02
20:19:11 EST"
[19] "2012-02-03 02:40:36 EST" "2012-02-03 20:17:56 EST" "2012-02-04
06:12:16 EST"
[22] "2012-02-05 08:05:02 EST"
table(format(x, "%H"))
02 04 05 06 07 08 14 15 20 21
1 3 3 1 1 2 1 2 4 4
It's possible that you may not realize that jim holman has implicitly
given you a handle on doing operations on such groups, since you could
use the value of format(x. "%H") as the indexing argument in tapply,
ave, or aggregate.
--
David.
On Sun, Feb 5, 2012 at 4:54 AM, Hasan Diwan <hasan.di...@gmail.com>
wrote:
I have a list of numbers corresponding to timestamps, a sample of
which follows:
c(1327211358, 1327221999, 1327527296, 1327555433, 1327701042,
1327761389, 1327780993, 1327815670, 1327822964, 1327897497,
1327897527,
1327937072, 1327938300, 1327957589, 1328044466, 1328127921,
1328157588,
1328213951, 1328236836, 1328300276, 1328335936, 1328429102)
I would like to group these into hours. In other words, something
like:
c( "2012-01-31 21:14:26 PST" "2012-02-01 20:25:21 PST"
"2012-02-02 04:39:48 PST" "2012-02-02 20:19:11 PST"
"2012-02-03 02:40:36 PST" "2012-02-03 20:17:56 PST"
"2012-02-04 06:12:16 PST" "2012-02-05 08:05:02 PST")
Hour Hits
21 1
20 3
4 1
2 1
6 1
8 1
How would I do this without too much pain (from a CPU perspective)?
This is a subset of a million entries and I would rather not go
through these manually... So, any advice? Many thanks! -- H
--
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Envoyait de mon portable
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
Jim Holtman
Data Munger Guru
What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
